An outcomes model of medical decision making

In the traditional fix-it model of medical decision making, the identified problem is typically characterized by a diagnosis that indicates a deviation from normalcy. When a medical problem is multifaceted and the available interventions are only partially effective, a broader vision of the health care endeavor is needed. What matters to the patient, and what should matter to the practitioner, is the patient's future possibilities. More specifically, what is important is the character of the alternative futures that the patient could have and choosing among them so as to achieve the best future possible, with the ranking of outcomes determined by the patient's preferences. This paper describes the fix-it model, presents and defends the outcomes-based model, and demonstrates that the latter is useful in developing normative conceptions of informed consent and decision making and in establishing a basis for societal involvement in the decision making process. Finally, several shortcomings of the model will be acknowledged.     

An integrative model of clinical-ethical decision making

The purpose of this paper is to propose a model of clinical-ethical decision making which will assist the health care professional to arrive at an ethically defensible judgment. The model highlights the integration between ethics and decision making, whereby ethics as a systematic analytic tool bring to bear the positive aspects of the decision making process. The model is composed of three major elements. The ethical component, the decision making component and the contextual component. The latter incorporates the relational aspects between the provider and the patient and the organizational structure. The model suggests that in order to arrive at an ethically, justifiable sound decision one make reference to those three elements.     

Multialternative decision field theory: a dynamic connectionist model of decision making

The authors interpret decision field theory (J. R. Busemeyer & J. T. Townsend, 1993) as a connectionist network and extend it to accommodate multialternative preferential choice situations. This article shows that the classic weighted additive utility model (see R. L. Keeney & H. Raiffa, 1976) and the classic Thurstone preferential choice model (see L. L. Thurstone, 1959) are special cases of this new multialternative decision field theory (MDFT), which also can emulate the search process of the popular elimination by aspects (EBA) model (see A. Tversky, 1969). The new theory is unique in its ability to explain several central empirical results found in the multialternative preference literature with a common set of principles. These empirical results include the similarity effect, the attraction effect, and the compromise effect, and the complex interactions among these three effects. The dynamic nature of the model also implies strong testable predictions concerning the moderating effect of time pressure on these three effects.     

Dual processes in decision making and developmental neuroscience: A fuzzy-trace model

From Piaget to the present, traditional and dual-process theories have predicted improvement in reasoning from childhood to adulthood, and improvement has been observed. However, developmental reversals—that reasoning biases emerge with development—have also been observed in a growing list of paradigms. We explain how fuzzy-trace theory predicts both improvement and developmental reversals in reasoning and decision making. Drawing on research on logical and quantitative reasoning, as well as on risky decision making in the laboratory and in life, we illustrate how the same small set of theoretical principles apply to typical neurodevelopment, encompassing childhood, adolescence, and adulthood, and to neurological conditions such as autism and Alzheimer’s disease. For example, framing effects—that risk preferences shift when the same decisions are phrased in terms of gains vs. losses—emerge in early adolescence as gist-based intuition develops. In autistic individuals, who rely less on gist-based intuition and more on verbatim-based analysis, framing biases are attenuated (i.e., they outperform typically developing control subjects). In adults, simple manipulations based on fuzzy-trace theory can make framing effects appear and disappear depending on whether gist-based intuition or verbatim-based analysis is induced. These theoretical principles are summarized and integrated in a new mathematical model that specifies how dual modes of reasoning combine to produce predictable variability in performance. In particular, we show how the most popular and extensively studied model of decision making—prospect theory—can be derived from fuzzy-trace theory by combining analytical (verbatim-based) and intuitive (gist-based) processes.     

A pattern recognition account of decision making

In the domain of pattern recognition, experiments have shown that perceivers integrate multiple sources of information in an optimal manner. In contrast, other research has been interpreted to mean that decision making is nonoptimal. As an example, Tversky and Kahneman (1983) have shown that subjects commit a conjunction fallacy because they judge it more likely that a fictitious person named Linda is a bank teller and a feminist than just a bank teller. This judgment supposedly violates probability theory, because the probability of two events can never be greater than the probability of either event alone. The present research tests the hypothesis that subjects interpret this judgment task as a pattern recognition task. If this hypothesis is correct, subjects’ judgments should be described accurately by the fuzzy logical model of perception (FLMP)—a successful model of pattern recognition. In the first experiment, the Linda task was extended to an expanded factorial design with five vocations and five avocations. The probability ratings were described well by the FLMP and described poorly by a simple probability model. The second experiment included (1) two fictitious people, Linda and Joan, as response alternatives and (2) both ratings and categorization judgments. Although the ratings were accurately described by both the FLMP and an averaging of the sources of information, the categorization judgments were described better by the FLMP. These results reveal important similarities in recognizing patterns and in decision making. Given that the FLMP is an optimal method for combining multiple sources of information, the probability judgments appear to be optimal in the same manner as pattern-recognition judgments.     

A dual-process approach to health risk decision making: The prototype willingness model

Although dual-process models in cognitive, personality, and social psychology have stimulated a large body of research about analytic and heuristic modes of decision making, these models have seldom been applied to the study of adolescent risk behaviors. In addition, the developmental course of these two kinds of information processing, and their relation to the development of self-regulation are not well understood at this time. The current paper reviews what leading dual-process models have to say about the development of analytic and heuristic decision making, and their implications for adolescent risk behavior. In addition, it reviews research on the prototype willingness model of adolescent decision making—a dual-process model designed specifically to address non-intentional, but volitional adolescent risk behavior. It also discusses the implications of dual-process models for intervention research.     

Computer-augmented decision making

The principal judgmental components of multiattribute decision making are examined here with specific reference to how these components can be captured electronically. Once captured, a function, rule, or algorithm may be executed for the integration of this information and the selection of the optimal alternative(s). Two kinds of algorithms are discussed: one based on linear models, the other on fuzzy-set theory and ratio scaling. With on-line support and certain assumptions about human biases (which lead to nonoptimal decisions), the quality of decisions can be enhanced considerably. The principal concerns are with end-user acceptance of computer augmented decisions.     

A lexicographic combination model of decision making by superintendents among multiattribute instructional program alternatives

The decision-making process of 16 superintendents in choosing among alternative instructional programs for elementary level grades was studied. The additive and lexicographic combination models of decision making were investigated for consistency with the process used by the Ss in ranking 27 alternative instructional programs. The programs were formed from all possible combinations of three different results on each of three attributes. The attributes were (1) program cost per pupil, (2) reading achievement gain in grade units, and (3) arithmetic achievement gain in grade units. Fifteen Ss performed with five or fewer pairwise reversals from the lexicographic model. The lexicographic model was accepted as most consistent with the decision-making process.     

Vocational choice: A decision making perspective

We propose a model of vocational choice that can be used for analyzing and guiding the decision processes underlying career and job choices. Our model is based on research in behavioral decision making (BDM), in particular the choice goals framework developed by Bettman, Luce, and Payne (1998). The basic model involves two major processes. First, the selection of a decision strategy according to four choice goals: maximizing decision accuracy, minimizing cognitive effort, minimizing negative emotion, and maximizing justifiability of the decision. Second, the construction of situation-specific preferences, which can reflect irrelevant task and context factors such as the evaluation mode. This basic model is extended to account for social influences and the long decision time typical of most career and job decisions. We review research on vocational choice in light of this model, discuss normative implications for counseling, and outline a research agenda for studying vocational choice from a behavioral decision making perspective.     

A neural cognitive model of argumentation with application to legal inference and decision making

Formal models of argumentation have been investigated in several areas, from multi-agent systems and artificial intelligence (AI) to decision making, philosophy and law. In artificial intelligence, logic-based models have been the standard for the representation of argumentative reasoning. More recently, the standard logic-based models have been shown equivalent to standard connectionist models. This has created a new line of research where (i) neural networks can be used as a parallel computational model for argumentation and (ii) neural networks can be used to combine argumentation, quantitative reasoning and statistical learning. At the same time, non-standard logic models of argumentation started to emerge. In this paper, we propose a connectionist cognitive model of argumentation that accounts for both standard and non-standard forms of argumentation. The model is shown to be an adequate framework for dealing with standard and non-standard argumentation, including joint-attacks, argument support, ordered attacks, disjunctive attacks, meta-level attacks, self-defeating attacks, argument accrual and uncertainty. We show that the neural cognitive approach offers an adequate way of modelling all of these different aspects of argumentation. We have applied the framework to the modelling of a public prosecution charging decision as part of a real legal decision making case study containing many of the above aspects of argumentation. The results show that the model can be a useful tool in the analysis of legal decision making, including the analysis of what-if questions and the analysis of alternative conclusions. The approach opens up two new perspectives in the short-term: the use of neural networks for computing prevailing arguments efficiently through the propagation in parallel of neuronal activations, and the use of the same networks to evolve the structure of the argumentation network through learning (e.g. to learn the strength of arguments from data).     

Toward a hermeneutic model of ethical decision making in clinical practice

Documented ethical violations and empirical research have demonstrated that, despite professional standards and formal training in ethical principles, some psychotherapists engage in unethical behaviors that compromise the welfare of clients. It appears that competing values and interests that emerge in the therapeutic endeavor can interfere with therapists' considerations of ethical standards and their willingness to act ethically. Expanding current models of ethical decision making, this article offers a hermeneutic model that recognizes that in addition to moral reasoning, the context of the therapeutic relationship and the therapist's subjective responses are fundamental considerations in the interpretation and application of ethical interventions. Implications for understanding and training of ethics in psychotherapy in this broader context are explored.     

Numeracy and decision making

A series of four studies explored how the ability to comprehend and transform probability numbers relates to performance on judgment and decision tasks. On the surface, the tasks in the four studies appear to be widely different; at a conceptual level, however, they all involve processing numbers and the potential to show an influence of affect. Findings were consistent with highly numerate individuals being more likely to retrieve and use appropriate numerical principles, thus making themselves less susceptible to framing effects, compared with less numerate individuals. In addition, the highly numerate tended to draw different (generally stronger or more precise) affective meaning from numbers and numerical comparisons, and their affective responses were more precise. Although generally helpful, this tendency may sometimes lead to worse decisions. The less numerate were influenced more by competing, irrelevant affective considerations. Analyses showed that the effect of numeracy was not due to general intelligence. Numerical ability appears to matter to judgments and decisions in important ways.     

Dynamic multi-criteria decision making

Most medium-and long-term decision making in industry and government can be viewed as dynamic multi-criteria decision making (MCDM), in which the decision makers are free to alter the emphasis placed on each objective in the light of developing circumstances. In this paper the problem of time-dependent weights in MCDM is discussed and an analysis of empirical data associated with dynamic decision making is presented.     

Personality components of decision making

Summary Relationships between proneness to behavioral stereotypy (Ster) measured in a problem-solving task (electromaze) and decision-making behavior (under conditions of risk and certainty, chance and skill) were investigated using 64 subjects. Subjects more stereotyped in the electromaze (Ster ⁺) tended to also be more stereotyped in their decision-making behavior. Ster was not related to extraversion, neuroticism, rigidity or overall electromaze performance, but Ster ^– more often required an excessive number of trials for task solution. The decision making of males tended to be more stereotyped. The results were discussed in terms of the construct validity and theoretical interpretation of Ster.

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Zusammenfassung Es wurden Beziehungen zwischen der Neigung zur Verhaltensstereotypie (Ster), die bei einer Problemlösungsaufgabe gemessen wurde, und dem Entscheidungsverhalten (mit und ohne Risiko, wobei der Erfolg sowohl durch den Zufall wie auch durch das Können der Vp bestimmt wurde) untersucht. Vpn, die sich im Electromaze stereotyp verhielten (Ster ⁺), verhielten sich auch bei ihren Entscheidungen stereotyp. Es wurden keine Beziehungen zwischen Ster und den Variablen Extraversion, Neurotizismus, Rigidität und Gesamtleistung im Electromaze gefunden, jedoch benötigten Ster ^– häufiger eine extrem lange Serie von Versuchen zur Aufgabenlösung. Die männliche Vpn neigten stärker dazu, in Entscheidungssituationen stereotyp zu reagieren. Die Ergebnisse wurden vom Standpunkt der Konstruktvalidität und der theoretischen Grundlage der Ster aus diskutiert.

     

Conditional mechanisms of decision making

Decision making is an important link in the central part of a reflex—the “mental element” according to Sechenov. The reflex nature of this mental process is revealed in experiments where a voluntary motor reaction is chosen unconsciously as a response to subliminal conditional visual stimuli. Thus, learning which is reflected by “advance” or prior decision making can be performed unconsciously through a conditional reflex. But, once elaborated, temporary connections are preserved only in shortterm memory. They are not transferred to long-term memory, as in the case of recognition of signals. Decision making, being the central mental part of the reflex, like any activity of the brain, is performed in time by a certain cortical structure. Analysis of P₃₀₀ amplitudes shows that decision making is related to local activation of the frontal parts of the cerebral hemispheres. We suggest that the local activation of these areas is induced by conditional excitation of the neuronal mechanisms of focused attention. It provides a “command” to perform a voluntary motor reaction adequate to the conditions at hand. A large part of latency of voluntary motor response of man is spent on decision making, especially in discrimination of signals and in choice of reactions.     

Knowledge management in decision making and decision support

A knowledge-oriented view of decisions and decision making is introduced, as a complement to classical perspectives and as a contribution of under-standing computer-based possibilities for relaxing strains on decision makers. This perspective includes a model of knowledge management activities performed by a decision maker and a taxonomy of knowledge types. It leads to a characterization of decision-support-system purpose, traits, and potentials that offers a basis for new research into computer-based possibilities for knowledge management. Clyde W. Holsapple holds the Rosenthal Endowed Chair in Management Information Systems and is Professor of Decision Science and Information Systems at the College of Business and Economics, University of Kentucky.